Detection system and user interface for a flow cytometer system

ABSTRACT

The detection system of the first preferred embodiment includes a detector, having a wide dynamic range, that receives photonic inputs from the interrogation zone and produces an analog signal; and an analog-to-digital converter (ADC), having a high bit resolution, that is coupled to the detector and converts an analog signal to a digital signal. The digital signal includes an initial data set of the full dynamic range of the input signals from the flow cytometer sample. The method of extracting and analyzing data from a flow cytometer system of the first preferred embodiment preferably includes the steps of: collecting a full dynamic range of input signals from a flow cytometer sample; recognizing and annotating aggregate particle events; and storing an initial data set and an annotated data set of the full dynamic range of the input signals from the flow cytometer sample.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.60/871,616, filed 22 Dec. 2006, which is incorporated in its entirety bythis reference.

TECHNICAL FIELD

The present invention relates generally to the field of flow cytometers,and more particularly to detection systems and user interfaces in thefield of flow cytometers.

BACKGROUND

One common problem in flow cytometry is the necessity for coincidencedetection in the presence of multiple particles that are closely spacedor joined in the sample. These closely spaced or joined particles areknow as “doublets” when two particles are together or “higher-orderaggregate particles” when three or more particles are together. Users offlow cytometry systems typically want to know if the sample containsaggregate particles. Depending on the experiment, aggregate particlescan either be undesirable (such as contaminants from poor samplepreparation) or desirable (such as cells in the process of celldivision/mitosis).

Conventional flow cytometry systems operate with a user interface thatmay include a doublet discrimination module (DDM) feature. When thisfeature is activated, the detection system can detect closely spaced orjoined particles, known in the art as “doublets”, via an algorithm thatcan recognize the characteristic “peak-trough-peak” waveform produced bydoublets. When a doublet event is detected, the DDM artificiallyincreases at least one of the parameter values to help the user moreeasily visualize and gate these events. This modification is notdesirable, however, because the data is not preserved exactly as it wasoriginally generated.

The limitations of the detection system and user interface of typicalflow cytometer systems with a DDM feature have at least twodisadvantages: (1) the potential loss of valuable original data becausethe DDM artificially increases at least one of the parameter values,modifying the data at the time of acquisition; and (2) the inability toobserve and “undo” changes made to the data by the DDM without runningadditional samples.

Accordingly, there is a need in the art to create a new and improveddetection system and user interface for a flow cytometer that avoids orminimizes these disadvantages. The present invention provides such newand improved detection system for a flow cytometer.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a schematic block diagram of a flow cytometer detection systemin accordance with a first preferred embodiment of the presentinvention.

FIGS. 2 and 3 are schematic block diagrams of a flow cytometer userinterface in accordance with the preferred embodiment of the presentinvention.

DESCRIPTION OF THE PREFERRED EMBODIMENT

The following description of the preferred embodiment of the inventionis not intended to limit the invention to this preferred embodiment, butrather to enable any person skilled in the art of flow cytometers tomake and use this invention.

As shown in FIGS. 1 and 2, the preferred embodiment of the inventionincludes a detection system 10 adapted to recognize and annotateaggregate particle events, and a user interface system 100 adapted toidentify, isolate, display, and/or analyze data including the annotatedhigher-order aggregate particle events.

1. Detection System

As shown in FIG. 1, the detection system 10 of the first preferredembodiment is preferably designed to be integrated into a flow cytometerhaving an interrogation zone 12. The detection system 10 of the firstpreferred embodiment allows for the recognition and annotation ofdoublets or higher-order aggregate particle events. The presentinvention makes it possible to preserve the measurements as they weredetected and to annotate the aggregate particle events for latervisualization or isolation for analysis. The detection system 10 hassufficient data capacity to process additional parameters such as onethat annotates each event as either an aggregate particle event or anon-aggregate particle event. The detection system 10 also includes analgorithm (implemented through hardware or software) that is able torecognize the characteristic “peak-trough-peak” waveform produced byaggregate particle events and annotate the events accordingly.

The detection system 10 includes a detector 14 adapted to receivephotonic inputs P from the interrogation zone 12 and produce an analogsignal, and an analog-to-digital converter (ADC) 20 coupled to thedetector 14 and adapted to convert an analog signal to a digital signal.The detector 14 has a dynamic range and the ADC 20 has a high bitresolution such that the detection system 10 has sufficient datacapacity to process additional parameters including one that recognizesand annotates aggregate particle events.

The detector 14 of the preferred embodiment functions to receivephotonic inputs from the interrogation zone and produce analog signalsbased on these photonic inputs. The detector 14 is preferably operableover a wide dynamic range. As used herein, the term “wide dynamic range”is preferably defined as greater than or equal to 100 dB. The detector14 preferably has a luminous sensitivity between 80 and 120 microampsper lumen, but may alternatively have a luminous sensitivity of anysuitable value. The detector 14 is preferably operable over a spectralrange of approximately 400 to 700 nanometers, but may alternatively beoperable over any suitable spectral range. Preferably, the detector 14includes one or more PIN photodiodes and a synchronous detection unit(not shown). The PIN photodiodes function to receive photonic inputs Pfrom an interrogation zone 12, and convert the impending electromagneticradiation into an electrical signal. Although a PIN photodiode ispreferred, the detector 14 may use other suitable detection devices witha wide dynamic range, such as specialized photomultipliers or otherphotodiodes. The synchronous detection unit functions to provide thefidelity for the input signals in the lower end of the signal range. Thesynchronous detection unit is preferably similar to the synchronousdetection unit disclosed in U.S. Ser. No. 10/198,378, filed 18 Jul. 2002and entitled “Flow Cytometer and Detection System of Lesser Size”, whichis incorporated in its entirety by this reference. Although thissynchronous detection unit is preferred, the detector 14 may use othersuitable signal conditioners. Further, in certain circumstances, thedetector 14 may omit the synchronous detection unit, which would yield acircuit with wide dynamic range, but less luminous sensitivity.

The detection system 10 of the preferred embodiment further includes anamplifier 16 that is coupled to the detector 14. The amplifier 16preferably receives the electrical signal of the detector 14 andamplifies the signal by a predetermined amount, depending upon thestrength of the output and the breadth of the detector range.Alternatively, the amplifier 16 may include variable attenuators suchthat the amplifier 16 applies a dynamically variable gain to the signal.Although the amplifier 16 preferably operates in the electrical domain,the amplifier 16 may alternatively operate in the optical domain. Forexample, the amplifier 16 may be integrated or partially integrated intothe detector 14, such as in the case of an avalanche photodiode (APD),which is an amplified photodetector known in the art. The preferredamplifier 16 has a signal-to-noise ratio (SNR) ranging betweenapproximately 100 dB and 120 dB.

The detection system 10 of the first preferred embodiment also includesan automatic gain control (AGC) unit 40. The AGC unit 40 is preferablycoupled to both an exciter 50 and the amplifier 16. Alternatively, theAGC unit 40 may be coupled to either the exciter 50 or the amplifier 16.Operating on the amplifier 16, the AGC unit 40 functions to dynamicallyvary the gain of the amplifier 16 with respect to the analog signalproduced by the detector 14. This dynamic gain control allows a singledetector 14 with limited dynamic range to track an input signal withmuch larger dynamic range. Operating on the exciter 50, the AGC unit 40functions to dynamically vary the output of the exciter 50, therebyvarying the signal excited in the interrogation zone 12 and by extensionthe optical properties of the photonic inputs P. The AGC unit 40 furtherfunctions to keep the generated signal within the dynamic range of thedetector 14. The AGC unit 40 may be integrated into the amplifier 16,the exciter 50, or both. Alternatively, the AGC unit may be remotelycoupled to the amplifier 16, the exciter 50 or both.

The detection system 10 of the first preferred embodiment furtherincludes a compression unit 18 that is coupled to the amplifier 16. Thecompression unit 18 functions to reduce the dynamic range of theplurality of electrical signals from the amplifier 16 and compress thatdata into an electrical signal with a smaller dynamic range that isappropriate for the ADC 20 of the preferred system. In the preferredembodiment, the detection system 10 incorporates signal compression toobtain better resolution for the input signals in the lower end of thesignal range. The compression unit 18 preferably uses a nonlinearcompression algorithm, such as a logarithmic compression algorithm, butmay use a linear, parametric, or any other suitable approach. Inalternative embodiments, the detection system 10 may omit thecompression unit 18.

The ADC 20 of the detection system 10 functions to convert an analogsignal into a digital signal that is readily usable by a digitalcircuit, processor, or computing device. The ADC 20 preferably includesa high bit resolution. As used herein, the term “high bit resolution” ispreferably defined as greater than or equal to 16-bits, and morepreferably defined as greater than or equal to 24-bits. The ADC 20preferably includes a Signal-to-Noise Ratio (SNR) of approximatelygreater than 100 dB, but may alternatively include a SNR of any suitablevalue.

The detection system 10 of the preferred embodiment preferablyinterfaces with an analysis engine 30, which functions to apply gain andscaling factors to the acquired data, independent of the acquisitionstep. The analysis engine 30 also includes an algorithm that is able torecognize aggregate particle events and annotate them throughout theacquisition step. The algorithm preferably recognizes the characteristic“peak-trough-peak” waveform produced by aggregate particle events andannotates the events accordingly while simultaneously preserving theraw, unmodified data. The algorithm may additionally or alternativelyrecognize other characteristic aspects, such as a unique width versusheight or area for the waveform. Each event is preferably labeled aseither an “aggregate particle event” or “doublet” or a “non-aggregateparticle event”, but may alternatively be labeled in any other suitablefashion such as labeling the number of aggregate particles, labeling adescriptor of the separation between the two particles (such as 20%conjoined or “loosely connected”) based on the peak versus troughratios, labeling if the aggregate particle is a contaminant, or labelingif the aggregate particle is a cell undergoing cell division or mitosis.

The analysis engine 30 may be configured as a software and/or hardwaremodule. In an alternative variation, the detection system 10 and theanalysis engine 30 may be physically separated. That is, the detectionsystem 10 might store raw, collected data (with aggregate particleevents annotated) on a memory device (such as a CD-ROM or other suchmedia), which can then be removed and/or transferred to the analysisengine 30 (such as a PC) for analysis. This approach has the advantageof minimizing the use time by each user of the detection system 10. Thecollection of the data in this manner eliminates the expenditure ofvaluable user time during the pre-set step and avoids the potential lossof valuable data.

2. User Interface

As shown in FIG. 2, the user interface 100 of the preferred embodimentof the invention extracts data from the full dynamic range of a flowcytometer in a single run and annotates specific events (such asdoublets or higher-order aggregate particle events) across the fulldynamic range, and then manipulates scaling and/or culling factors andallows for the identification, isolation, and/or analysis of theannotated events across the full dynamic range after the data have beencollected. The data of the full dynamic range are collected and storedin raw or unmodified form during the acquisition step with the aggregateparticle events identified and then the user interface can display theunmodified data and/or modified data. Because scaling and/or cullingfactors can be applied and the identification, isolation, and/oranalysis of the annotated events can be completed after the acquisitionstep is complete, the user interface facilitates real-time comparisonsbetween the raw and modified data on a single, unique sample run. Thisadditionally allows for the reversible discrimination of aggregateparticle events at any point in the analysis of the collected, labeleddata. Scaling and/or culling and the identification, isolation, and/oranalysis of the annotated events can be adjusted or undone without theneed to re-run pilot samples, which saves time, reduces the amount ofsample required, and eliminates the potential of lost data due toincorrect gain settings or identification, isolation, and/or analysis ofthe annotated events.

As shown in FIG. 2, the flow cytometer user interface of the preferredembodiment includes the steps of (a) running the sample and saving allcollected data (102), (b) viewing the raw (or “unmodified”) data (104),(c) modifying the raw data (106) (e.g., scaling and/or culling the rawdata), (d) reviewing and saving the modified settings (108), and (e)exporting the saved data (110). Once the sample has been run and allcollected data have been saved, the user can repeat the steps ofmodifying the raw data, saving the modified settings, and exporting thesaved data as many times as necessary or desirable without the need torun an additional sample.

As shown in FIG. 3, the flow cytometer user interface of the preferredembodiment includes the steps of collecting a full dynamic range ofinput signals from a flow cytometer sample (102′), storing an initialdata set of the full dynamic range of the input signals from the flowcytometer sample (102″), recognizing aggregate particle events in theinitial data set (106′), annotating aggregate particle events in theinitial data set (106″), storing an annotated data set of the fulldynamic range of the input signals from the flow cytometer sample(108′), and displaying at least one of the initial data set and theannotated data set (104′). The step of recognizing aggregate particleevents in the initial data set preferably occurs substantiallysimultaneously with collecting a full dynamic range of input signalsfrom a flow cytometer sample. The flow cytometer user interface of thepreferred embodiment further includes the steps of allowing modificationof at least one of the initial data set and the annotated data set(106′″), reviewing and saving the modified data set (108), and exportingthe saved data set (110).

The user interface of the preferred embodiment is coupled to thedetection system 10 of the preferred embodiment, but may alternativelybe coupled to any suitable diagnostic and/or analysis system. In analternative embodiment, the user interface is in electroniccommunication with a composite of several narrow dynamic range flowcytometers.

In the preferred embodiment, the first step of ‘running the sample andsaving all collected data’ (102) includes the collection (i.e.,acquisition) and electronic storage of the full dynamic range of inputsignals (in raw, unmodified format) from a flow cytometer sample withthe aggregate particle events recorded with annotation such that theycan be identified and/or culled from the other event data for thepurposes of analysis and display. The full dynamic range of inputsignals is preferably defined as the range of input signals thatprovides a 1:100,000 ratio, and more preferably a 1:1,000,000 ratio,between the faintest objects and the brightest objects. The full dynamicrange of input signals is preferably captured by a 24 bit process, whichtranslates to roughly 16,700,000 levels of information, but mayalternatively be captured by any suitable process. Preferably, thecaptured data includes an error rate induced by electric noise of lessthan one-percent. In the preferred embodiment, the data are collected ina raw, unmodified format without the use of, or the adjustment in, thegain level of the detector. The collection of the data in this mannereliminates the expenditure of valuable user time and avoids thepotential loss of valuable data through misconfiguration of the system.

The data collected in the first step, includes the information collectedfrom the algorithm that is able to recognize aggregate particle eventsand annotate them. The algorithm recognizes the characteristic“peak-trough-peak” waveform produced by aggregate particle events (oranother unique aspect of the waveform) and annotates the eventsaccordingly, creating an annotated data set, while simultaneouslypreserving the raw, unmodified data (the initial data set). Each eventis preferably labeled as either an “aggregate particle event” or“doublet” or a “non-aggregate particle event”, but may alternatively belabeled in any other suitable fashion such as labeling the number ofaggregate particles, labeling a descriptor of the separation between thetwo particles (such as 20% conjoined or “loosely connected”) based onthe peak versus trough ratios, labeling if the aggregate particle is acontaminant, or labeling if the aggregate particle is a cell undergoingcell division or mitosis. This labeling information is collected andstored along with the full dynamic range of input signals (in raw,unmodified format) from a flow cytometer sample.

The second step of ‘viewing the raw data’ (104) permits the user toobserve the raw data and annotated data that has been collected andstored from the sample run and identify the anticipated appropriatemodifications for the sample and the possible identification, isolation,and/or analysis of the annotated events. In the preferred embodiment,the user interface presents the raw data after the acquisition iscomplete. In an alternative embodiment, the user interface presents theraw data during the acquisition step. In a first “local” variation ofthe preferred embodiment, the original, raw data set to be viewed isacquired from a flow cytometer coupled to the user interface; in asecond “remote” variation, the original data set is acquired from anelectronic storage medium. When the user interface is coupled to a broaddynamic range flow cytometer, as in the preferred embodiment, the userinterface can display data from greater than four decades of signal.

The third step of ‘modifying the raw data’ (106) permits the user tomanipulate (e.g. scale and/or cull) the data collected across the fulldynamic range of input signals from the flow cytometer sample and toidentify, isolate, and/or analyze the annotated events. In this step,the user interface permits the user to perform real-time comparisonsbetween the raw and modified data on a single, unique sample run.Additionally, scaling and/or culling and the identification, isolation,and/or analysis of the annotated events can be adjusted or undonewithout the need to re-run pilot samples allowing multiple adjustmentson the same initial data set.

In the preferred embodiment, the user scales, culls, isolates, and/oranalyzes the raw data to select a subset of signals and/or aggregateparticle events that correspond to the desired sample population. Theuser is permitted to apply gain and scaling factors to the acquired dataor perform any other suitable analysis in order to review the occurrenceand the features of the aggregate particle events. This is performedindependently of the acquisition step and permits the user to adjust thebounds of the data and analyze the data. In an alternative embodiment,the user interface automatically scales and/or culls the raw data andperforms an analysis on the annotated data based on an appropriatealgorithm. In this alternative embodiment, the user interface may accepta user command that corresponds to, or identifies, the desired samplepopulation. The modifying of raw data preferably occurs after dataacquisition is complete, and multiple signal gain/scaling adjustmentscan be made on a single, unique data set.

The user interface of the preferred embodiment may be virtual, physical,or any suitable combination. In the virtual variation, the knobs,sliders, and other controls are shown only on a display and not in aphysical unit. The controls, whether virtual or physical, permit thesingle, unique data set to be modified in a step-wise, sequentialfashion. Alternatively, the user interface may permit the single, uniquedata to be repeatedly or iteratively modified. Scaling is preferablyapplied hierarchically based on forward scatter, which can be expandedto include any or all of the available data channels (scatter andfluorescent) in a progressive fashion. Scaling may, however, be appliedin any suitable manner.

Any number of subsets of data can be generated that correspond to one ormore sample populations contained within the raw data set. Preferably,the user interface permits each subset (i.e. modification) of the rawdata and the settings used to generate the desired subset of data to beindividually saved, recorded, and identified. Alternatively, the userinterface may permit subsets of raw data that are generated bysequential or iterative modifications and the settings used to generatethe desired subset of data to be saved and identified at each iterationand in their totality.

In the preferred embodiment, the user interface utilizes one or moregraphical, menu-driven formats that can accept and display data sets,such as those from a flow cytometer with broad dynamic range. In analternative embodiment, the user interface utilizes a numerical displayformat. The user interface permits the modification of its displayrepresentation through the application of scaling and/or culling factorsto the original data set or through the analysis of data sets toinclude, exclude, and/or combine data based on the annotated aggregateparticle events. In a first variation, the user interface simultaneouslypresents modified and raw representations of a single data set. In asecond variation, the user interface simultaneously presents multipledata sets that can be simultaneously viewed, compared, and analyzed. Theuser can undo or otherwise alter the modifications of one or more datasets using the menu-driven options.

The user interface of the preferred embodiment represents raw data andmodified data using any suitable format, including graphically andnumerically. The user interface enables observation of the consequencesof scaling, culling, or analysis modifications on a unique data set bysimultaneous representation of raw and modified data. For example,aggregate particle events can be displayed in plots as a unique color orcan be “scrubbed” (or removed) from the data set for statisticalanalysis of non-aggregate particle events. In one variation, separategraphs are generated from the raw and modified data and are displayed inseparate frames, which preferably represents a preview of theexport/print version of the viewed data. In an alternative variation,the raw and modified data are superimposed on one another in the samegraph frame, with each data set preferably distinguished by color and/orshading. In yet another variation, the consequences of each modificationapplied to the raw data in the generation of the modified data arerepresented in independent planes of the same graph frame, and allmodifications can be superposed.

The fourth step of ‘reviewing and saving the modified settings’ (108)permits the user to identify the modifications made to the original dataset and to store the setting(s) used to generate the desired subset ofdata, thus allowing the user to save both the data and the correspondingscaling, culling, and/or analysis parameters. The user interfaceprovides virtual instrument settings that can be adjusted, whichgenerate a corresponding subset of data from the raw (i.e. original)data set. The user can repeat the steps of modifying the raw data andsaving the desired subset of data and modified settings as many times asnecessary and/or desirable, without the need for running additionalsample through the flow cytometer. If the user generates the subset ofdata by making one or more alterations in the virtual settings, the usercan access the previously saved alterations made to the subset of dataand retrace or “undo” the alterations sequentially. In the preferredembodiment, the user interface will prompt the user to save the modifiedsubset of data, the settings used to generate the data, and any otherpertinent information regarding the sample or data acquisition; in analternative embodiment, the data settings are saved automatically. Theuser interface can apply hierarchical scaling factors to independentdata channels (e.g. scatter channels and fluorescent channels).

The fifth step of ‘exporting the saved data’ (110) permits the user totransfer the original (raw) data set and/or the modified subset of datafrom the flow cytometer system to a different medium, such as a printoutor an electronic file. The data may be transferred to any suitablemedium for subsequent viewing, analysis, and/or storage, and thesettings used to generate the data and other pertinent informationregarding the sample or data acquisition may also be included.

The flow cytometer user interface of the preferred embodiment mayfurther include the step of acting upon the information previouslygenerated. In one version, the flow cytometer user interface mayautomatically chose whether or not to sort a particular cell based onwhether it is a doublet. In another version, the flow cytometer userinterface may automatically signal to the user upon the occurrence (oromission) of a particular number of “aggregate particle events” during aparticular time period, or upon a particular rise or drop in the ratioof “aggregate particle events” to “non-aggregate particle events”. Theflow cytometer user interface may, of course, perform or initial anysuitable action based on any suitable measurement or parameter derivedfrom the use of the flow cytometer user interface.

As a person skilled in the art of flow cytometry will recognize from theprevious detailed description and from the figures and claims,modifications and changes can be made to the preferred embodiment of theinvention without departing from the scope of this invention defined inthe following claims.

1. A detection system for a flow cytometer having an interrogation zone,comprising: a detector that receives photonic inputs from theinterrogation zone and produces an analog signal, the detector having awide dynamic range; and an analog-to-digital converter (ADC), coupled tothe detector, that converts an analog signal to a digital signal, theADC having a high bit resolution; wherein the digital signal includes aninitial data set of the full dynamic range of the input signals from theflow cytometer sample.
 2. The detection system of claim 1 furthercomprising an analysis engine that recognizes aggregate particle eventsin the initial data set and annotates the recognized aggregate particleevents, thereby creating an annotated data set of the full dynamic rangeof the input signals from the flow cytometer sample.
 3. The detectionsystem of claim 2 wherein the analysis engine recognizes a“peak-trough-peak” waveform produced by aggregate particle events andannotates the recognized aggregate particle events, thereby creating anannotated data set of the full dynamic range of the input signals fromthe flow cytometer sample.
 4. The detection system of claim 3 whereinthe analysis engine labels an aggregate particle event as an “aggregateparticle event” and a non-aggregate particle event as a “non-aggregateparticle event”.
 5. The detection system of claim 1 wherein the high bitresolution of the ADC is defined as greater than or equal to 16-bits. 6.The detection system of claim 1 wherein the wide dynamic range of thedetector is defined as greater than or equal to 100 dB.
 7. A method ofextracting and analyzing data from a flow cytometer system comprisingthe steps of: collecting a full dynamic range of input signals from aflow cytometer sample; storing an initial data set of the full dynamicrange of the input signals from the flow cytometer sample; recognizingaggregate particle events in the initial data set; annotating aggregateparticle events in the initial data set; storing an annotated data setof the full dynamic range of the input signals from the flow cytometersample; and displaying at least one of the initial data set and theannotated data set.
 8. The method of claim 7 wherein recognizingaggregate particle events in the initial data set occurs substantiallysimultaneously with collecting a full dynamic range of input signalsfrom a flow cytometer sample.
 9. The method of claim 7 whereinrecognizing aggregate particle events in the initial data set includesidentifying a “peak-trough-peak” waveform produced by aggregate particleevents.
 10. The method of claim 9 wherein annotating aggregate particleevents in the initial data set includes labeling an aggregate particleevent as an “aggregate particle event” and a non-aggregate particleevent as a “non-aggregate particle event”.
 11. The method of claim 10wherein annotating aggregate particle events in the initial data setincludes further labeling an aggregate particle event with the number ofaggregate particles in the event.
 12. The method of claim 7 furthercomprising the steps of: allowing modification of at least one of theinitial data set and the annotated data set; saving the modified dataset; and exporting the saved data set.
 13. The method of claim 12wherein displaying at least one of the initial data set and theannotated data set includes permitting a user to observe at least one ofthe initial data set and the annotated data set from the full dynamicrange of input signals, and permitting the user to identify theappropriate modifications for at least one of the initial data set andthe annotated data set.
 14. The method of claim 12 wherein allowingmodification of at least one of the initial data set and the annotateddata set includes permitting the user to manipulate at least one of theinitial data set and the annotated data set across the full dynamicrange of input signals from the flow cytometer sample and to generate amodified data set.
 15. The method of claim 14 wherein allowingmodification of at least one of the initial data set and the annotateddata set further includes permitting the user to: perform real-timecomparisons between the initial data set, the annotated data set, andthe modified data set on a single flow cytometer sample; adjust or undomodifications, to make multiple adjustments on the same initial data setor annotated data set; and generate at least one subset of data thatcorresponds to one or more sample populations contained within at leastone of the initial data set and the annotated data set.
 16. The methodof claim 15 wherein allowing modification of at least one of the initialdata set and the annotated data set further includes permitting the userto: isolate at least one of the annotated aggregate particle events andthe annotated non-aggregate particle events; and remove the annotatedaggregate particle events or the annotated non-aggregate particleevents.
 17. The method of claim 9 wherein allowing modification of atleast one of the initial data set and the annotated data set furtherincludes providing adjustable virtual instrument settings.
 18. Themethod of claim 9 wherein allowing modification of at least one of theinitial data set and the annotated data set further includes utilizing agraphical, menu-driven format that accepts and displays data sets. 19.The method of claim 18 wherein utilizing a graphical, menu-driven formatincludes displaying separate graphs that are generated from the initialdata set, the annotated data set, and the modified data set in separateframes.
 20. The method of claim 19 wherein aggregate particle events aredisplayed in a first color and non-aggregate particle events aredisplayed in a second color.